OpenRaiser/Intern-Atlas huggingface dataset:
Comparison of Ant-Inspired Gatherer Allocation Approaches using Memristor-Based Environmental Models
Venue: arXiv cs.NE 2013
Year: 2013

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasing overall efficiency and decreasing time to fully deplete an environment, however it only works well when the resources are of similar quality. The Leaf Cutter method, based on Leaf Cutter Ant behaviour, assigns all gatherers first to the best resource, and once depleted, uses the All Site model to spread them out amongst the rest. The Leaf Cutter model is better at increasing resource influx in the short-term and vastly out-performs the All Site model in a more varied environments. It is demonstrated that memristor based abstractions of gatherer models provide potential methods for both the comparison and implementation of agent controls.
A Family of Five-Weight Cyclic Codes and Their Weight Enumerators
Venue: arXiv cs.IT 2013
Year: 2013

Cyclic codes are a subclass of linear codes and have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this paper, a family of $p$-ary cyclic codes whose duals have three zeros are proposed. The weight distribution of this family of cyclic codes is determined. It turns out that the proposed cyclic codes have five nonzero weights.
Improved Accuracy of PSO and DE using Normalization: an Application to Stock Price Prediction
Venue: arXiv cs.NE 2013
Year: 2013

Data Mining is being actively applied to stock market since 1980s. It has been used to predict stock prices, stock indexes, for portfolio management, trend detection and for developing recommender systems. The various algorithms which have been used for the same include ANN, SVM, ARIMA, GARCH etc. Different hybrid models have been developed by combining these algorithms with other algorithms like roughest, fuzzy logic, GA, PSO, DE, ACO etc. to improve the efficiency. This paper proposes DE-SVM model (Differential EvolutionSupport vector Machine) for stock price prediction. DE has been used to select best free parameters combination for SVM to improve results. The paper also compares the results of prediction with the outputs of SVM alone and PSO-SVM model (Particle Swarm Optimization). The effect of normalization of data on the accuracy of prediction has also been studied.
Generalizing determinization from automata to coalgebras
Venue: arXiv cs.LO 2013
Year: 2013

The powerset construction is a standard method for converting a nondeterministic automaton into a deterministic one recognizing the same language. In this paper, we lift the powerset construction from automata to the more general framework of coalgebras with structured state spaces. Coalgebra is an abstract framework for the uniform study of different kinds of dynamical systems. An endofunctor F determines both the type of systems (F-coalgebras) and a notion of behavioural equivalence (~_F) amongst them. Many types of transition systems and their equivalences can be captured by a functor F. For example, for deterministic automata the derived equivalence is language equivalence, while for non-deterministic automata it is ordinary bisimilarity. We give several examples of applications of our generalized determinization construction, including partial Mealy machines, (structured) Moore automata, Rabin probabilistic automata, and, somewhat surprisingly, even pushdown automata. To further witness the generality of the approach we show how to characterize coalgebraically several equivalences which have been object of interest in the concurrency community, such as failure or ready semantics.
Lightweight Lempel-Ziv Parsing
Venue: arXiv cs.DS 2013
Year: 2013

We introduce a new approach to LZ77 factorization that uses O(n/d) words of working space and O(dn) time for any d >= 1 (for polylogarithmic alphabet sizes). We also describe carefully engineered implementations of alternative approaches to lightweight LZ77 factorization. Extensive experiments show that the new algorithm is superior in most cases, particularly at the lowest memory levels and for highly repetitive data. As a part of the algorithm, we describe new methods for computing matching statistics which may be of independent interest.
Local Redesigning of Airspace Sectors
Venue: arXiv cs.CG 2013
Year: 2013

In this paper we study the Airspace Sectorization Problem (ASP) where the goal is to find an optimal partition (sectorization) of the airspace into a certain number of sectors, each managed by an air traffic controller. The objective of the ASP is to find a "well-balanced" sectorization that distributes the workload evenly among the controllers. We formulate the ASP as a partitioning problem of a set of moving points in a polygonal domain. In addition to the requirement of balancing the workload, we introduce restrictions on the geometry of the sectorization which come from the Air Traffic Management aspects. We investigate several versions of the problem that arise from different definitions of the notion of the workload and various choices of geometric restrictions on the sectorization. We conclude that most of the formulations of the problem, except maybe in some trivial cases, are NP-hard. Finally, we propose a Local Redesigning Method (LRM), a heuristic algorithm that rebalances a given sectorization by adjusting the boundaries of the sectors. We evaluate LRM experimentally on synthetically generated scenarios as well as on the real historical traffic data. We demonstrate that the sectorizations produced by our method are superior in comparison with the current sectorizations of the US airspace.
Source Code Analysis to Remove Security Vulnerabilities in Java Socket Programs: A Case Study
Venue: arXiv cs.CR 2013
Year: 2013

This paper presents the source code analysis of a file reader server socket program (connection-oriented sockets) developed in Java, to illustrate the identification, impact analysis and solutions to remove five important software security vulnerabilities, which if left unattended could severely impact the server running the software and also the network hosting the server. The five vulnerabilities we study in this paper are: (1) Resource Injection, (2) Path Manipulation, (3) System Information Leak, (4) Denial of Service and (5) Unreleased Resource vulnerabilities. We analyze the reason why each of these vulnerabilities occur in the file reader server socket program, discuss the impact of leaving them unattended in the program, and propose solutions to remove each of these vulnerabilities from the program. We also analyze any potential performance tradeoffs (such as increase in code size and loss of features) that could arise while incorporating the proposed solutions on the server program. The proposed solutions are very generic in nature, and can be suitably modified to correct any such vulnerabilities in software developed in any other programming language. We use the Fortify Source Code Analyzer to conduct the source code analysis of the file reader server program, implemented on a Windows XP virtual machine with the standard J2SE v.7 development kit.
Sparse Channel Estimation for MIMO-OFDM Amplify-and-Forward Two-Way Relay Networks
Venue: arXiv cs.IT 2013
Year: 2013

Accurate channel impulse response (CIR) is required for coherent detection and it can also help improve communication quality of service in next-generation wireless communication systems. One of the advanced systems is multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) amplify and forward two-way relay networks (AF-TWRN). Linear channel estimation methods, e.g., least square (LS), have been proposed to estimate the CIR. However, these methods never take advantage of channel sparsity and then cause performance loss. In this paper, we propose a sparse channel estimation method to exploit the sparse structure information in the CIR at each end user. Sparse channel estimation problem is formulated as compressed sensing (CS) using sparse decomposition theory and the estimation process is implemented by LASSO algorithm. Computer simulation results are given to confirm the superiority of proposed method over the LS-based channel estimation method.
Towards the Rapid Development of a Natural Language Understanding Module
Venue: arXiv cs.CL 2013
Year: 2013

When developing a conversational agent, there is often an urgent need to have a prototype available in order to test the application with real users. A Wizard of Oz is a possibility, but sometimes the agent should be simply deployed in the environment where it will be used. Here, the agent should be able to capture as many interactions as possible and to understand how people react to failure. In this paper, we focus on the rapid development of a natural language understanding module by non experts. Our approach follows the learning paradigm and sees the process of understanding natural language as a classification problem. We test our module with a conversational agent that answers questions in the art domain. Moreover, we show how our approach can be used by a natural language interface to a cinema database.
MGSim - Simulation tools for multi-core processor architectures
Venue: arXiv cs.AR 2013
Year: 2013

MGSim is an open source discrete event simulator for on-chip hardware components, developed at the University of Amsterdam. It is intended to be a research and teaching vehicle to study the fine-grained hardware/software interactions on many-core and hardware multithreaded processors. It includes support for core models with different instruction sets, a configurable multi-core interconnect, multiple configurable cache and memory models, a dedicated I/O subsystem, and comprehensive monitoring and interaction facilities. The default model configuration shipped with MGSim implements Microgrids, a many-core architecture with hardware concurrency management. MGSim is furthermore written mostly in C++ and uses object classes to represent chip components. It is optimized for architecture models that can be described as process networks.
A new greedy randomized adaptive search procedure for multiobjective RNA structural alignment
Venue: arXiv cs.DS 2013
Year: 2013

RNA secondary structures prediction is one of the main issues in bioinformatics. It seeks to elucidate structural conserved regions within a set of RNA sequences. Unfortunately, finding an accurate conserved structure is a very hard task to do. Within the present study, the prediction problem is considered as a multiobjective optimization process in which the structural conservation and the sensitivity of the multiple alignment are optimized. The proposed method called GRASPMORSA is based on an aggregate function and GRASP procedure. The initial solutions are obtained by using a random progressive local/ global algorithm, and then they are refined by an iterative realignment. Experiments within a large scale of data have shown the efficacy and effectiveness of the proposed method and its capacity to reach good quality solutions.
Investigate The Performance Evaluation of IPTV over WiMAX Networks
Venue: arXiv cs.NI 2013
Year: 2013

Deployment Video on Demand (VoD) over the next generation (WiMAX) has become one of the intense interest subjects in the research these days, and is expected to be the main revenue generators in the near future and the efficiency of video streaming over next generation 4G is the key to enabling this. We are considering video streaming for real time video was coded by different H.264.x codes (H.264/AVC, and SVC), and we consider an IP-Unicast to deliver this streaming video over WiMAX. Our approach investigates the performance evaluation of IPTV (VoD) over WiMAX networks. OPNET is used to investigate the performance of VoD over WiMAX. Results obtained from simulation indicate that SVC video codec is an appropriate video codec for video streaming over WiMAX.
Analytical and Numerical Characterizations of Shannon Ordering for Discrete Memoryless Channels
Venue: arXiv cs.IT 2013
Year: 2013

This paper studies several problems concerning channel inclusion, which is a partial ordering between discrete memoryless channels (DMCs) proposed by Shannon. Specifically, majorization-based conditions are derived for channel inclusion between certain DMCs. Furthermore, under general conditions, channel equivalence defined through Shannon ordering is shown to be the same as permutation of input and output symbols. The determination of channel inclusion is considered as a convex optimization problem, and the sparsity of the weights related to the representation of the worse DMC in terms of the better one is revealed when channel inclusion holds between two DMCs. For the exploitation of this sparsity, an effective iterative algorithm is established based on modifying the orthogonal matching pursuit algorithm.
Rate-Privacy in Wireless Sensor Networks
Venue: arXiv cs.NI 2013
Year: 2013

This paper introduces the concept of rate privacy in the context of wireless sensor networks. Our discussion reveals that the concept indeed is of a great importance for the privacy preservation of such networks. As a result, we propose a buffering scheme to protect the rate from adversaries. Simulation results verify the applicability of our approach.
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Venue: arXiv cs.AI 2013
Year: 2013

Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expressed locally in Bayesian networks through convex sets of distributions. Two approaches for combination of local models are considered. The first approach takes the largest set of joint distributions that is compatible with the local sets of distributions; we show how to reduce this type of robust inference to a linear programming problem. The second approach takes the convex hull of joint distributions generated from the local sets of distributions; we demonstrate how to apply interior-point optimization methods to generate posterior bounds and how to generate approximations that are guaranteed to converge to correct posterior bounds. We also discuss calculation of bounds for expected utilities and variances, and global perturbation models.
Limitations of Skeptical Default Reasoning
Venue: arXiv cs.AI 2013
Year: 2013

Poole has shown that nonmonotonic logics do not handle the lottery paradox correctly. In this paper we will show that Pollock's theory of defeasible reasoning fails for the same reason: defeasible reasoning is incompatible with the skeptical notion of derivability.
Network Fragments: Representing Knowledge for Constructing Probabilistic Models
Venue: arXiv cs.AI 2013
Year: 2013

In most current applications of belief networks, domain knowledge is represented by a single belief network that applies to all problem instances in the domain. In more complex domains, problem-specific models must be constructed from a knowledge base encoding probabilistic relationships in the domain. Most work in knowledge-based model construction takes the rule as the basic unit of knowledge. We present a knowledge representation framework that permits the knowledge base designer to specify knowledge in larger semantically meaningful units which we call network fragments. Our framework provides for representation of asymmetric independence and canonical intercausal interaction. We discuss the combination of network fragments to form problem-specific models to reason about particular problem instances. The framework is illustrated using examples from the domain of military situation awareness.
Representing Aggregate Belief through the Competitive Equilibrium of a Securities Market
Venue: arXiv cs.AI 2013
Year: 2013

We consider the problem of belief aggregation: given a group of individual agents with probabilistic beliefs over a set of uncertain events, formulate a sensible consensus or aggregate probability distribution over these events. Researchers have proposed many aggregation methods, although on the question of which is best the general consensus is that there is no consensus. We develop a market-based approach to this problem, where agents bet on uncertain events by buying or selling securities contingent on their outcomes. Each agent acts in the market so as to maximize expected utility at given securities prices, limited in its activity only by its own risk aversion. The equilibrium prices of goods in this market represent aggregate beliefs. For agents with constant risk aversion, we demonstrate that the aggregate probability exhibits several desirable properties, and is related to independently motivated techniques. We argue that the market-based approach provides a plausible mechanism for belief aggregation in multiagent systems, as it directly addresses self-motivated agent incentives for participation and for truthfulness, and can provide a decision-theoretic foundation for the "expert weights" often employed in centralized pooling techniques.
Fast Value Iteration for Goal-Directed Markov Decision Processes
Venue: arXiv cs.AI 2013
Year: 2013

Planning problems where effects of actions are non-deterministic can be modeled as Markov decision processes. Planning problems are usually goal-directed. This paper proposes several techniques for exploiting the goal-directedness to accelerate value iteration, a standard algorithm for solving Markov decision processes. Empirical studies have shown that the techniques can bring about significant speedups.
Public Key Exchange Using Matrices Over Group Rings
Venue: arXiv cs.CR 2013
Year: 2013

We offer a public key exchange protocol in the spirit of Diffie-Hellman, but we use (small) matrices over a group ring of a (small) symmetric group as the platform. This "nested structure" of the platform makes computation very efficient for legitimate parties. We discuss security of this scheme by addressing the Decision Diffie-Hellman (DDH) and Computational Diffie-Hellman (CDH) problems for our platform.
Uncovering the Wider Structure of Extreme Right Communities Spanning Popular Online Networks
Venue: arXiv cs.SI 2013
Year: 2013

Recent years have seen increased interest in the online presence of extreme right groups. Although originally composed of dedicated websites, the online extreme right milieu now spans multiple networks, including popular social media platforms such as Twitter, Facebook and YouTube. Ideally therefore, any contemporary analysis of online extreme right activity requires the consideration of multiple data sources, rather than being restricted to a single platform. We investigate the potential for Twitter to act as a gateway to communities within the wider online network of the extreme right, given its facility for the dissemination of content. A strategy for representing heterogeneous network data with a single homogeneous network for the purpose of community detection is presented, where these inherently dynamic communities are tracked over time. We use this strategy to discover and analyze persistent English and German language extreme right communities.
Terrorist Network: Towards An Analysis
Venue: arXiv cs.SI 2013
Year: 2013

Terrorist network is a paradigms to understand the terrorism. The terrorist involves a lot of people, and among them are involved as perpetrators, but on the contrary it is very difficult to know who they are caused by lack of information. Network structure is used to reveal other things about the terrorist beyond the ability of social sciences.
The Capacity Region of the Wireless Ergodic Fading Interference Channel with Partial CSIT to Within One Bit
Venue: arXiv cs.IT 2013
Year: 2013

Fundamental capacity limits are studied for the two-user wireless ergodic fading IC with partial Channel State Information at the Transmitters (CSIT) where each transmitter is equipped with an arbitrary deterministic function of the channel state (this model yields a full control over how much state information is available). One of the main challenges in the analysis of fading networks, specifically multi-receiver networks including fading ICs, is to obtain efficient capacity outer bounds. In this paper, a novel capacity outer bound is established for the two-user ergodic fading IC. For this purpose, by a subtle combination of broadcast channel techniques (i.e., manipulating mutual information functions composed of vector random variables by Csiszar-Korner identity) and genie-aided techniques, first a single-letter outer bound characterized by mutual information functions including some auxiliary random variables is derived. Then, by novel arguments the derived bound is optimized over its auxiliaries only using the entropy power inequality. Besides being well-described, our outer bound is efficient from several aspects. Specifically, it is optimal for the fading IC with uniformly strong interference. Also, it is sum-rate optimal for the channel with uniformly mixed interference. More importantly, it is proved that when each transmitter has access to any amount of CSIT that includes the interference to noise ratio of its non-corresponding receiver, the outer bound differs by no more than one bit from the achievable rate region given by Han-Kobayashi scheme. This result is viewed as a natural generalization of the ETW to within one bit capacity result for the static channel to the wireless ergodic fading case.
Relational Access Control with Bivalent Permissions in a Social Web/Collaboration Architecture
Venue: arXiv cs.SI 2013
Year: 2013

We describe an access control model that has been implemented in the web content management framework "Deme" (which rhymes with "team"). Access control in Deme is an example of what we call "bivalent relation object access control"(BROAC). This model builds on recent work by Giunchiglia et al. on relation-based access control (RelBAC), as well as other work on relational, flexible, fine-grained, and XML access control models. We describe Deme's architecture and review access control models, motivating our approach. BROAC allows for both positive and negative permissions, which may conflict with each other. We argue for the usefulness of defining access control rules as objects in the target database, and for the necessity of resolving permission conflicts in a social Web/collaboration architecture. After describing how Deme access control works, including the precedence relations between different permission types in Deme, we provide several examples of realistic scenarios in which permission conflicts arise, and show how Deme resolves them. Initial performance tests indicate that permission checking scales linearly in time on a practical Deme website.